Red Teaming (AI Security Testing)

Red teaming is a structured adversarial testing method where a team of security experts deliberately attempts to expose vulnerabilities, failure modes, or harmful behaviors in an AI system — mirroring the approach of a real attacker. The term originates from military planning, where a red team would simulate enemy forces to stress-test defenses. In the AI context, red teaming involves systematic attempts to manipulate a model through adversarial prompts, jailbreaks, and edge-case inputs — trying to coax the system into producing harmful content, leaking sensitive information, or bypassing safety guardrails. These tests typically occur before public deployment as part of a safety evaluation lifecycle. Leading AI labs like Anthropic, OpenAI, and Google DeepMind publish red teaming findings as part of their model cards and system cards. Regulatory frameworks including the EU AI Act now recommend adversarial testing for high-risk AI deployments.